Data Mining Algorithms in SSAS, Excel, and R

Don't use data mining as a black box. Get a deep understanding of how the data mining algorithms work. This knowledge is not only theoretical; it helps you developing better models in production.
Course info
Rating
(135)
Level
Intermediate
Updated
Jul 24, 2015
Duration
2h 59m
Table of contents
Introduction to Data Mining
Naive Bayes and Decision Trees
Linear Regression, Regression Trees, and Support Vector Machines
Linear Regression, Neural Network, and Models Evaluation
Time Series
Clustering
Association Rules and Sequence Clustering
Description
Course info
Rating
(135)
Level
Intermediate
Updated
Jul 24, 2015
Duration
2h 59m
Description

Data mining is gaining popularity as the most advanced data analysis technique. With modern data mining engines, products, and packages, like SQL Server Analysis Services (SSAS), Excel, and R, data mining has become a black box. It is possible to use data mining without knowing how it works. However, not knowing how the algorithms work might lead to many problems, including using the wrong algorithm for a task, misinterpretation of the results, and more. This course explains how the most popular data mining algorithms work, when to use which algorithm, and advantages and drawbacks of each algorithm as well. Demonstrations show the algorithms usage in SSAS, Excel, and R.

About the author
About the author

Dejan Sarka, MCT and SQL Server MVP, is an independent consultant, trainer, and developer focusing on database & business intelligence applications. His specialties are advanced topics like data modeling, data mining, and data quality.

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Section Introduction Transcripts
Section Introduction Transcripts

Naive Bayes and Decision Trees
Hello. I am Dejan Sarka, and this is Data Mining Algorithms in SSAS, Excel, and R course. This is the second module, and the title of the module is Naive Bayes and Decision Trees. As you can imagine from the title, in this module I'm going to introduce the Naive Bayes algorithm and then I'm going to switch to the decision trees algorithm. I will show demos for both algorithms as well. After the last demo, I will make a summary of this module.

Linear Regression, Regression Trees, and Support Vector Machines
Hello, I'm Dejan Sarka, and this is the Data Mining in SQL Server Analysis Services, Excel and R course. This is module 3, and the title of the module is Linear Regression, Regression Trees, Support Vector Machines. From the title you can imagine what I'm going to talk about. I will describe the linear regression algorithm, and then move to regression trees and finish with support vector machines. After demos in Analysis Services, Excel, and R, I will make a brief summary of this model.

Linear Regression, Neural Network, and Models Evaluation
Hello, I'm Dejan Sarka, and this is the Data Mining and SQL Server Analysis Services, Excel and R course. This is module 4, Neural Network, Logistic Regression, Predictive Models Evaluation. Again, you can imagine from the title of the module what I'm going to talk about. I will describe the neural network algorithm, the logistic regression algorithm, and then show you how you can evaluate predictive models to select the one that you will use in production. After demos I will make a brief summary.

Time Series
Hello, I'm Dejan Sarka, and this is the Data Mining Algorithms in SQL Server Analysis Services, Excel and R course. This is module 5, and the name of the module is Time Series. In this module I'm going to introduce the specific data preparation for time series and then two Time Series algorithms, ARTXP and ARIMA. After demos, I will make a brief summary.

Clustering
Hi, I'm Dejan Sarka, and this is the Data Mining Algorithms in SQL Server Analysis Services, Excel and R course. This is module 6, Clustering. In this module, I'm going to introduce different clustering algorithms, so I will introduce Hierarchical Clustering, K-Means, and Expectation-Maximization algorithms. I will do demos for each algorithm and then summarize the module.

Association Rules and Sequence Clustering
Hi, I'm Dejan Sarka, and this is the Data Mining Algorithms in SQL Server Analysis Services, Excel and R course. This is the seventh, also the last module of this course, and the title is Association Rules and Sequence Clustering. Again, you can imagine from the title what I will be talking about. I will describe the Association Rules algorithm, and then go in depth with Sequence Clustering algorithm, and after some demos make a summary.